Scilab Function
Last update : 31/10/2003

st_deviation - standard deviation (row or column-wise) of vector/matrix entries

stdev - standard deviation (row or column-wise) of vector/matrix entries

### Calling Sequence

  `y=st_deviation(x)`
  `y=st_deviation(x,'r')`
  `y=st_deviation(x,'c')`
  `y=stdev(x)`
  `y=stdev(x,'r')`
  `y=stdev(x,'c')`

### Parameters

- `x`: real vector or matrix
- `y`: scalar or vector

### Description

st_deviation computes the "sample" standard deviation, that is, it is normalized by N-1, where N is the sequence length.

For a vector or a matrix `x`, `y=st_deviation(x)` returns in the scalar `y` the standard deviation of all the entries of `x`.

`y=st_deviation(x,'r')` (or, equivalently, `y=st_deviation(x,1)`) is the rowwise standard deviation. It returns in each entry of the column vector `y` the standard deviation of each row of `x`.

`y=st_deviation(x,'c')` (or, equivalently, `y=st_deviation(x,2)`) is the columnwise st_deviation. It returns in each entry of the row vector `y` the standard deviation of each column of `x`.

### Examples

    A=[1,2,10;7,7.1,7.01];
    st_deviation(A)
    st_deviation(A,'r')
    st_deviation(A,'c')

### See Also

`sum`, `median`, `mean`, `nanstdev`, `stdevf`,